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Answer Presentation with Contextual Information: A Case Study Using Syntactic and Semantic Models

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AI 2015: Advances in Artificial Intelligence (AI 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9457))

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Abstract

Answer presentation is a subtask in Question Answering that investigates the ways of presenting an acquired answer to the user in a format that is close to a human generated answer. In this research we explore models to retrieve additional, relevant, contextual information corresponding to a question and present an enriched answer by integrating the additional information as natural language. We investigate the role of Bag of Words (BoW) and Bag of Concepts (BoC) models to retrieve the relevant contextual information. The information source utilized to retrieve the information is a Linked Data resource, DBpedia, which encodes large amounts of knowledge corresponding to Wikipedia in a structured form as triples. The experiments utilizes the QALD question sets consisted of training and testing sets each containing 100 questions. The results from these experiments shows that pragmatic aspects, which are often neglected by BoW (syntactic models) and BoC (semantic models), form a critical part of contextual information selection.

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References

  1. Perera, R.: IPedagogy: question answering system based on web information clustering. In: T4E 2012 (2012)

    Google Scholar 

  2. Perera, R.: Scholar: cognitive computing approach for question answering. Honours thesis, University of Westminster (2012)

    Google Scholar 

  3. Perera, R., Nand, P.: Interaction history based answer formulation for question answering. In: Klinov, P., Mouromtsev, D. (eds.) KESW 2014. CCIS, vol. 468, pp. 128–139. Springer, Heidelberg (2014)

    Google Scholar 

  4. Mendes, A.C., Coheur, L.: When the answer comes into question in question-answering: survey and open issues. Nat. Lang. Eng. 19(01), 1–32 (2013)

    Article  Google Scholar 

  5. Gelbukh, A., Sidorov, G., Lavin-Villa, E., Chanona-Hernandez, L.: Automatic term extraction using log-likelihood based comparison with general reference corpus. In: Hopfe, C.J., Rezgui, Y., Métais, E., Preece, A., Li, H. (eds.) NLDB 2010. LNCS, vol. 6177, pp. 248–255. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  6. Perera, R., Nand, P.: Real text-CS - corpus based domain independent content selection model. In: ICTAI 2014, pp. 599–606 (2014)

    Google Scholar 

  7. Perera, R., Nand, P.: The role of linked data in content selection. In: Pham, D.-N., Park, S.-B. (eds.) PRICAI 2014. LNCS, vol. 8862, pp. 573–586. Springer, Heidelberg (2014)

    Google Scholar 

  8. Benamara, F., Dizier, P.S.: Dynamic generation of cooperative natural language responses in webcoop. In: 9th European Workshop on Natural Language Generation, Budapest, Hungary, ACL (2003)

    Google Scholar 

  9. Bosma, W.: Extending answers using discourse structure. In: Recent Advances in Natural Language Processing, Borovets, Bulgaria, Association for Computational Linguistics (2005)

    Google Scholar 

  10. Demner-Fushman, D., Lin, J.: Answer extraction, semantic clustering, and extractive summarization for clinical question answering. In: Proceedings of the 21st International Conference on Computational Linguistics and the 44th Annual Meeting of the ACL - ACL 2006, Morristown, NJ, USA, pp. 841–848. Association for Computational Linguistics, July 2006

    Google Scholar 

  11. Yu, H., Lee, M., Kaufman, D., Ely, J., Osheroff, J.A., Hripcsak, G., Cimino, J.: Development, implementation, and a cognitive evaluation of a definitional question answering system for physicians. J. Biomed. Inform. 40, 236–251 (2007)

    Article  Google Scholar 

  12. Cao, Y., Liu, F., Simpson, P., Antieau, L., Bennett, A., Cimino, J.J., Ely, J., Yu, H.: AskHERMES: an online question answering system for complex clinical questions. J. Biomed. Inform. 44, 277–288 (2011)

    Article  Google Scholar 

  13. Vargas-Vera, M., Motta, E.: AQUA – ontology-based question answering system. In: Monroy, R., Arroyo-Figueroa, G., Sucar, L.E., Sossa, H. (eds.) MICAI 2004. LNCS (LNAI), vol. 2972, pp. 468–477. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  14. Perera, R., Nand, P.: A multi-strategy approach for lexicalizing linked open data. In: Gelbukh, A. (ed.) CICLing 2015. LNCS, vol. 9042, pp. 348–363. Springer, Heidelberg (2015)

    Google Scholar 

  15. Perera, R., Nand, P.: Realtext-lex: a lexicalization framework for linked open data. In: ISWC 2015 Demonstration (2015)

    Google Scholar 

  16. Perera, R., Nand, P.: Generating lexicalization patterns for linked open data. In: Second Workshop on Natural Language Processing and Linked Open Data Collocated with 10th Recent Advances in Natural Language Processing (RANLP) (2015)

    Google Scholar 

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Authors and Affiliations

  1. School of Computer and Mathematical Sciences, Auckland University of Technology, Auckland, 1010, New Zealand

    Rivindu Perera & Parma Nand

Authors
  1. Rivindu Perera
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  2. Parma Nand
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Corresponding author

Correspondence to Rivindu Perera .

Editor information

Editors and Affiliations

  1. The University of Waikato, Hamilton, New Zealand

    Bernhard Pfahringer

  2. The Australian National University, Canberra, Aust Capital Terr, Australia

    Jochen Renz

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Perera, R., Nand, P. (2015). Answer Presentation with Contextual Information: A Case Study Using Syntactic and Semantic Models. In: Pfahringer, B., Renz, J. (eds) AI 2015: Advances in Artificial Intelligence. AI 2015. Lecture Notes in Computer Science(), vol 9457. Springer, Cham. https://doi.org/10.1007/978-3-319-26350-2_42

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  • DOI: https://doi.org/10.1007/978-3-319-26350-2_42

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26349-6

  • Online ISBN: 978-3-319-26350-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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